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dropEst - Pipeline

Pipeline for estimating molecular count matrices for droplet-based single-cell RNA-seq measurements. If you used the pipeline in your research, please cite the corresponding paper. To reproduce results from the paper see this repository.


For detailed explanations, please see the documentation


If you have problems with installation, please look at the Troubleshooting page and open an issue if there is nothing.


[0.8.6] - 2019-08-01

  • Added support for Drop-seq and CEL-Seq2

See Changelog for the full list.

General processing steps

  1. dropTag: extraction of cell barcodes and UMIs from the library. Result: demultiplexed .fastq.gz files, which should be aligned to the reference.
  2. Alignment of the demultiplexed files to reference genome. Result: .bam files with the alignment.
  3. dropEst: building count matrix and estimation of some statistics, necessary for quality control. Result: .rds file with the count matrix and statistics. Optionally: count matrix in MatrixMarket format.
  4. dropReport - Generating report on library quality.
  5. dropEstR - UMI count corrections, cell quality classification


Complete examples of the pipeline can be found at

Here are results of processing of neurons_900 10x dataset.

Supported protocols

  • 10x
  • CEL-Seq2
  • Drop-seq
  • iCLIP
  • inDrop (v1-3)
  • Seq-Well
  • SPLiT-seq


If you find this pipeline useful for your research, please consider citing the paper:

Petukhov, V., Guo, J., Baryawno, N., Severe, N., Scadden, D. T., Samsonova, M. G., & Kharchenko, P. V. (2018). dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments. Genome biology, 19(1), 78. doi:10.1186/s13059-018-1449-6

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